prostrate myself at the face of black

Author: ev-br

torch_np/_dtypes_impl.py

@@ -123,7 +123,7 @@ def nep50_to_tensors(x1, x2, handle_weaks):
             if cat_weak == 1 and cat_not_weak == 1:
                 # integers
                 iinfo = torch.iinfo(not_weak.dtype)
-                if weak < iinfo.min or weak > iinfo.max: 
+                if weak < iinfo.min or weak > iinfo.max:
                     raise OverflowError(
                         f"Python integer {weak} out of bounds for {not_weak.dtype}"
                     )

torch_np/_ufuncs.py

@@ -32,8 +32,18 @@ def _ufunc_postprocess(result, out, casting):
 ]
 
 
-NEP50_FUNCS = ("add", "subtract", "multiply", "floor_divide", "remainder", "bitwise_and", "bitwise_or", "bitwise_xor", "left_shift", "right_shift")
-
+NEP50_FUNCS = (
+    "add",
+    "subtract",
+    "multiply",
+    "floor_divide",
+    "remainder",
+    "bitwise_and",
+    "bitwise_or",
+    "bitwise_xor",
+    "left_shift",
+    "right_shift",
+)
 
 
 def deco_binary_ufunc(torch_func):
@@ -58,8 +68,10 @@ def wrapped(
         signature=None,
         extobj=None,
     ):
-        flag = (torch_func.__name__ in NEP50_FUNCS and
-                _dtypes_impl.default_dtypes == _dtypes_impl.default_dtypes_numpy)
+        flag = (
+            torch_func.__name__ in NEP50_FUNCS
+            and _dtypes_impl.default_dtypes == _dtypes_impl.default_dtypes_numpy
+        )
         x1, x2 = _dtypes_impl.nep50_to_tensors(x1, x2, flag)
 
         if dtype is None:

torch_np/tests/test_nep50_examples.py

@@ -4,6 +4,7 @@
 
 try:
     import numpy as _np
+
     HAVE_NUMPY = True
 except ImportError:
     HAVE_NUMPY = False
@@ -99,14 +100,21 @@ def test_nep50_exceptions(example):
         assert result.dtype == new.dtype
 
 
-
 # ### Directly compare to numpy ###
 
 weaks = [True, 1, 2.0, 3j]
-non_weaks = [tnp.asarray(True),
-             tnp.uint8(1), tnp.int8(1), tnp.int32(1), tnp.int64(1),
-             tnp.float32(1), tnp.float64(1),
-             tnp.complex64(1), tnp.complex128(1)]
+non_weaks = [
+    tnp.asarray(True),
+    tnp.uint8(1),
+    tnp.int8(1),
+    tnp.int32(1),
+    tnp.int64(1),
+    tnp.float32(1),
+    tnp.float64(1),
+    tnp.complex64(1),
+    tnp.complex128(1),
+]
+
 
 @pytest.mark.skipif(not HAVE_NUMPY, reason="NumPy not found")
 @pytest.mark.parametrize("scalar, array", itertools.product(weaks, non_weaks))
@@ -121,6 +129,5 @@ def test_direct_compare(scalar, array):
         assert result.dtype == result_numpy.dtype
         assert result == result_numpy
 
-
     finally:
         _np._set_promotion_state(state)